Scalable SAT Solving and its Application | Experimental Data
Description
Experimental data accompanying the doctoral thesis of Dominik P. Schreiber entitled "Scalable SAT Solving and its Application", Karlsruhe Institute of Technology, 2023.
Upstream URL: https://github.com/domschrei/sssaia
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Funding notices:
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 882500).
Some of this work was performed on the supercomputer ForHLR funded by the Ministry of Science, Research and the Arts Baden-W ̈urttemberg and by the Federal Ministry of Education and Research.
Some of this work was performed on the HoreKa supercomputer funded by the Ministry of Science, Research and the Arts Baden-Württemberg and by the Federal Ministry of Education and Research.
The author gratefully acknowledges the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de).
Files
sssaia.zip
Files
(104.1 MB)
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Additional details
Related works
- Is version of
- Dataset: https://github.com/domschrei/sssaia (URL)